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ACL
2007
15 years 7 months ago
A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
Feiyu Xu, Hans Uszkoreit, Hong Li
BMCBI
2008
173views more  BMCBI 2008»
15 years 6 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
JUCS
2006
185views more  JUCS 2006»
15 years 6 months ago
The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States
We outline the Berlin Brain-Computer Interface (BBCI), a system which enables us to translate brain signals from movements or movement intentions into control commands. The main co...
Benjamin Blankertz, Guido Dornhege, Steven Lemm, M...
BMCBI
2010
140views more  BMCBI 2010»
15 years 3 months ago
An improved machine learning protocol for the identification of correct Sequest search results
Background: Mass spectrometry has become a standard method by which the proteomic profile of cell or tissue samples is characterized. To fully take advantage of tandem mass spectr...
Morten Kallberg, Hui Lu
LCN
2006
IEEE
16 years 12 days ago
Training on multiple sub-flows to optimise the use of Machine Learning classifiers in real-world IP networks
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...
Thuy T. T. Nguyen, Grenville J. Armitage